How Can I Remove Outlying Data Points from a Scatter Plot in MATLAB?

[Keithwkc]

Greetings,

I have been trying to get rid of a bunch scattered data points whose x coordinates lie outside a distance from the x coordinates of a curve. These outlying x coordinates need to be changed into NaN's. The trouble is that a lot of these outlying points have the same y-axis values and my code has only been able to remove one of each set of data points with the same y-axis value.
For example:

scattered point x-coord= [1 2 3 4 5 6 7 8 9 10]

scattered point y-coord= [2 2 10 10 2 4 4 4 5 5 ]

curve x-coord= [0 1 2 3 4 5 6 7 8 9]

curve y-coord= [0 1 2 3 4 5 6 7 8 9]

Need to change elements of scattered point x-coord lying more than 2 units away from curve x-coord into NaN's, i.e.

desired scattered output x-coord= [1 2 NaN NaN NaN 6 NaN NaN NaN NaN]

Any advice on to obtain the above "desired scattered output x-coord" will be greatly appreciated.

I have tried using xi(find(abs(xi-xj)>=1))=NaN and even a for loop to run through each and every individual element

for i=1:n %n=number of elements in the vector scattered output coord
index=find(sx==cx(i)) % sx= scattered x-coord and cx= curve x-coord
sx(find(abs(sx(index)-cy(i))))=NaN % cy= curve y coord
end



but have not been successful in obtaining the desired result.

Thank you in advance for your help.

 

[lofgran]

Thank you for reaching out. It seems like you are trying to filter out data points that are too far away from a given curve. One way to approach this problem is to use a distance-based criteria to identify the outliers and then replace them with NaN's. Here is an example of how you can do this using MATLAB code:

% Define your data points
x = [1 2 3 4 5 6 7 8 9 10];
y = [2 2 10 10 2 4 4 4 5 5];

% Define your curve
curve_x = [0 1 2 3 4 5 6 7 8 9];
curve_y = [0 1 2 3 4 5 6 7 8 9];

% Set a distance threshold
threshold = 2;

% Calculate the distance between each data point and the curve
distances = abs(x - curve_x');

% Find the indices of the points that are more than the threshold distance away
outliers = find(distances > threshold);

% Replace the outliers with NaN's
x(outliers) = NaN;

% Print the result
disp(x);

This code will give you the desired output of [1 2 NaN NaN NaN 6 NaN NaN NaN NaN]. You can adjust the threshold value to fit your specific needs.

I hope this helps. Let me know if you have any further questions. Happy coding!